https://store-images.s-microsoft.com/image/apps.32243.82b7f195-ec83-4631-b68c-2f40e3e566a9.550e0223-ccf2-47ce-9137-89b42c608fcc.473f82c6-5a3e-427b-a259-cffca43bbf7f

SQBM+ for Azure Learn & Development Plan

東芝デジタルソリューションズ株式会社 (本社)

SQBM+ for Azure Learn & Development Plan

東芝デジタルソリューションズ株式会社 (本社)

A combinatorial optimization solver built on the quantum-inspired Simulated Bifurcation Algorithm.

Nov.1, 2024
The subscription problem has been resolved. You can subscribe SQBM+ at this moment.


Oct.22, 2024
We are experiencing a problem when we try to subscribe to SQBM+ at this time. We are currently working to resolve this issue by the end of October. We apologize for the inconvenience that may have caused.


SQBM+ is a set of solvers enabling users to quickly obtain nearly optimal solutions for large (e.g. millions of variables) combinatorial optimization problems, such as:
Portfolio optimization and risk management in financial service - 3D protein structure prediction in drug discovery process
Factory shift optimization in manufacturing or warehouse management
Key features:
Quickly obtains good approximate solutions for large optimization problems (QUBO, QPLIB and PUBO).
Suitable for QUBO problems with up to 10 million variables for the current version
Easy to use. Complicated parameter setting is not required.
SQBM is developed based on the theory described in the following papers:
Goto, H. et al. Combinatorial optimization by simulating adiabatic bifurcations in nonlinear Hamiltonian systems. Science Advances. 2019, 5, 4, eaav2372.
Goto, H. et al. High-performance combinatorial optimization based on classical mechanics. Science Advances. 2021, 7, 6, eabe7953.